@article{wang_rao_kwatra_milliken_dong_gomes_martin_catete_isvik_barnes_et al._2023, title={A Case Study on When and How Novices Use Code Examples in Open-Ended Programming}, url={https://doi.org/10.1145/3587102.3588774}, DOI={10.1145/3587102.3588774}, abstractNote={Many students rely on examples when learning to program, but they often face barriers when incorporating these examples into their own code and learning the concepts they present. As a step towards designing effective example interfaces that can support student learning, we investigate novices' needs and strategies when using examples to write code. We conducted a study with 12 pairs of high school students working on open-ended game design projects, using a system that allows students to browse examples based on their functionality, and to view and copy the example code. We analyzed interviews, screen recordings, and log data, identifying 5 moments when novices request examples, and 4 strategies that arise when students use examples. We synthesize these findings into principles that can inform the design of future example systems to better support students.}, journal={PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL 1}, author={Wang, Wengran and Rao, Yudong and Kwatra, Archit and Milliken, Alexandra and Dong, Yihuan and Gomes, Neeloy and Martin, Sarah and Catete, Veronica and Isvik, Amy and Barnes, Tiffany and et al.}, year={2023}, pages={82–88} }
 @article{milliken_catete_limke_gransbury_chipman_dong_barnes_2021, title={Exploring and Influencing Teacher Grading for Block-based Programs through Rubrics and the GradeSnap Tool}, DOI={10.1145/3446871.3469762}, abstractNote={This article examines the grading process and profiles of secondary computer science teachers as they assess block-based student programming submissions. Through an iterative design process, we have created a new tool, Gradesnap, which streamlines how teachers can open, review, and evaluate student submissions within the same interface. Our study compares teachers’ grading processes using the different assessment formats, so that we can understand how their grading processes can be augmented or supported to reduce ’pain points’ and to enable teachers to provide more constructive and formative feedback for students. We use a case study approach to examine the experiences and outcomes of four secondary computer science teachers with varied teaching and assessment experience, when grading as usual, grading with a rubric, and grading with GradeSnap. Our study shows that when participants use GradeSnap, they are able to give supportive comments to lower performing and borderline students who need critical feedback to better understand misconceptions. We also discovered that the different grading processes provided a vehicle for reflection for some teachers in understanding their grading goals and how they enact them. This research is the first to examine teacher grading processes for computer science, and highlights the need for teacher preparation and support for providing programming feedback and assessment.}, journal={ICER 2021: PROCEEDINGS OF THE 17TH ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH}, author={Milliken, Alexandra and Catete, Veronica and Limke, Ally and Gransbury, Isabella and Chipman, Hannah and Dong, Yihuan and Barnes, Tiffany}, year={2021}, pages={101–114} }
 @article{dong_shabrina_marwan_barnes_2021, title={You Really Need Help: Exploring Expert Reasons for Intervention During Block-based Programming Assignments}, DOI={10.1145/3446871.3469764}, abstractNote={In recent years, research has increasingly focused on developing intelligent tutoring systems that provide data-driven support for students in need of assistance during programming assignments. One goal of such intelligent tutors is to provide students with quality interventions comparable to those human tutors would give. While most studies focused on generating different forms of on-demand support, such as next-step hints and worked examples, at any given moment during the programming assignment, there is a lack of research on why human tutors would provide different forms of proactive interventions to students in different situations. This information is critical to know to allow the intelligent programming environments to select the appropriate type of student support at the right moment. In this work, we studied human tutors’ reasons for providing interventions during two introductory programming assignments in a block-based environment. Three human tutors evaluated a sample of 86 struggling moments identified from students’ log data using a data-driven model. The human tutors specified whether and why an intervention was needed (or not) for each struggling moment. We analyzed the expert tags and their consensus discussions and extracted three main reasons that made the experts decide to intervene: “missing key components to make progress”, “using wrong or unnecessary blocks”, “misusing needed blocks”, “having critical logic errors”, “needing confirmation and next steps”, and “unclear student intention”. We use six case studies to illustrate specific student code trace examples and the tutors’ reasons for intervention. We also discuss the potential types of automatic interventions that could address these cases. Our work sheds light on when and why students might need programming interventions. These insights contribute towards improving the quality of automated, data-driven support in programming learning environments.}, journal={ICER 2021: PROCEEDINGS OF THE 17TH ACM CONFERENCE ON INTERNATIONAL COMPUTING EDUCATION RESEARCH}, author={Dong, Yihuan and Shabrina, Preya and Marwan, Samiha and Barnes, Tiffany}, year={2021}, pages={334–346} }
 @inproceedings{lytle_cateté_dong_boulden_akram_houchins_barnes_wiebe_2019, place={Chengdu, Sichuan, China}, title={CEO: A Triangulated Evaluation of a Modeling-Based CT-Infused CS Activity for Non-CS Middle Grade Students}, ISBN={9781450362597}, url={http://dx.doi.org/10.1145/3300115.3309527}, DOI={10.1145/3300115.3309527}, abstractNote={With the increased demand for introducing computational thinking (CT) in K-12 classrooms, educational researchers are developing integrated lesson plans that can teach CT fundamentals in non-computing specific classrooms. Although these lessons reach more students through the core curriculum, proper evaluation methods are needed to ensure the quality of the design and integration. As part of a research practice partnership, we work to infuse research-backed curricula into science courses. We find a three-pronged approach of evaluation can help us make better decisions on how to improve experimental curricula for active classrooms. This CEO model uses three data sources (student code traces, exit ticket responses, and field observations) as a triangulated approach that can be used to identify programming behavior among novice developers, preferred task ordering for the assignment, and scaffolding recommendations to teachers. This approach allows us to evaluate the practical implementations of our initiative and create a focused approach for designing more effective lessons.}, booktitle={Proceedings of the ACM Conference on Global Computing Education  - CompEd '19}, publisher={ACM Press}, author={Lytle, Nicholas and Cateté, Veronica and Dong, Yihuan and Boulden, Danielle and Akram, Bita and Houchins, Jennifer and Barnes, Tiffany and Wiebe, Eric}, year={2019}, pages={58–64} }
 @article{catete_lytle_dong_boulden_akram_houchins_barnes_wiebe_lester_mott_et al._2018, title={Infusing Computational Thinking into Middle Grade Science Classrooms: Lessons Learned}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85056713650&partnerID=MN8TOARS}, DOI={10.1145/3265757.3265778}, abstractNote={There is a growing need to present all students with an opportunity to learn computer science and computational thinking (CT) skills during their primary and secondary education. Traditionally, these opportunities are available outside of the core curriculum as stand-alone courses often taken by those with preparatory privilege. Researchers have identified the need to integrate CT into core classes to provide equitable access to these critical skills. We have worked in a research-practice partnership with two magnet middle schools focused on digital sciences to develop and implement computational thinking into life sciences classes. In this report, we present initial lessons learned while conducting our design-based implementation research on integrating computational thinking into middle school science classes. These case studies suggest that several factors including teacher engagement, teacher attitudes, student prior experience with CS/CT, and curriculum design can all impact student engagement in integrated science-CT lessons.}, journal={WIPSCE'18: PROCEEDINGS OF THE 13TH WORKSHOP IN PRIMARY AND SECONDARY COMPUTING EDUCATION}, publisher={ACM Press}, author={Catete, Veronica and Lytle, Nicholas and Dong, Yihuan and Boulden, Danielle and Akram, Bita and Houchins, Jennifer and Barnes, Tiffany and Wiebe, Eric and Lester, James and Mott, Bradford and et al.}, year={2018}, pages={109–114} }
 @article{dong_barnes_2017, title={Evaluation of a Template-based Puzzle Generator for an Educational Programming Game}, DOI={10.1145/3102071.3106347}, abstractNote={Although there has been much work on procedural content generation for other game genres, very few researchers have tackled automated content generation for educational games. In this paper, we present a template-based, automatic puzzle generator for an educational puzzle programming game called BOTS. Two experts created their own new puzzles and evaluated generator-generated puzzles for meeting the educational goals, the structural and visual novelty. We show that our generator can generate puzzles with expert-designed educational goals while saving experts more than 80% of creation time, and these puzzles exhibit structural and visual novelty compared to expert-created puzzles. The contribution of this work is defined and implemented the first template-based automatic puzzle generator that saves expert time while incorporating expert-designed educational goals and enhancing puzzle creativity.}, journal={PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON THE FOUNDATIONS OF DIGITAL GAMES (FDG'17)}, author={Dong, Yihuan and Barnes, Tiffany}, year={2017} }